This is of course a first step, and questions on the role of imagination in this setup remain to be further explored. Specifically, questions such as how imagination can become involved in learning (imagination-based learning) and also in the modeled adversarial interactions, is yet to be answered in future research. Adversarially learned inference [1]} can be used as one particular approach to such future studies. In particular,
adversarially learned inference uses imagination to drive learning, exemplifying a broader class of imagination-based learning models that have been studied in cognitive science [2]}.
Another broad issue concerns how to evaluate the performance of the model and check the functional and structural constraints. Therefore, another interesting direction for future work is to seek for a suitable evaluation method, which would allow for model validation as an important step. Finally, the possibility of generalizing the proposed adversarial framework to other types of hallucination would also be of interest.
